openwhispr README

OpenWhispr

The open-source and free alternative to WisprFlow and Granola.
Privacy-first voice-to-text dictation with AI agents, meeting transcription, and notes. Cross-platform for macOS, Windows, and Linux.

Website · Docs · Download · API · Changelog

OpenWhispr turns your voice into text, notes, and actions from your desktop. Press a hotkey, speak, and your words appear at your cursor. Choose between fully private offline transcription with local speech-to-text models like Orukeet, Whisper, NVIDIA Parakeet, and Cohere Transcribe — where your audio never leaves your device — or cloud processing for speed. No data collection, no telemetry, fully open source.

Download

Platform	Download
macOS (Apple Silicon)	`.dmg`
macOS (Intel) *	`.dmg`
Windows	`.exe`
Linux	`.AppImage` / `.deb` / `.rpm` / `.tar.gz`

* On Intel Macs, live speaker identification and voice fingerprinting are unavailable: they depend on ONNX Runtime, which stopped shipping macOS x86_64 binaries in 1.24. Meetings still record and transcribe normally, and notes search falls back to keyword matching instead of semantic search.

Features

Voice dictation — global hotkey to dictate into any app with automatic pasting
Dictation translation — dedicated hotkey to dictate in one language and paste the text in another
AI agent — talk to GPT-5, Claude, Gemini, Groq, Tinfoil, OpenRouter, or local models with a named voice assistant
Voice Assistant hotkey — dedicated hotkey that sends what you say straight to your AI assistant as a command, no wake word needed and no cleanup pass; highlighted text is edited in place. With auto-paste enabled, answers paste at a focused text cursor or stream into a floating panel and copy to the clipboard when no writable cursor is available. You can also opt in to sending a screenshot of your current screen as context
Meeting transcription — auto-detect Zoom, Teams, and FaceTime calls with live speaker diarization, voice fingerprinting, and Google, Microsoft, or Apple Calendar integration
Local speaker diarization — on-device speaker labelling with voice fingerprint recognition across meetings, no cloud required
Notes — create, organize, and search notes with folders, semantic search, cloud sync, and AI actions
Team spaces & sharing — free for signed-in users; share notes on the web with link, domain, or invite-only visibility, and collaborate in team spaces with roles, invitations, and server-enforced membership
Audio import — transcribe existing audio and video: drag in files, batch-upload, or paste a YouTube/audio URL, with optional speaker detection
Local or cloud — your choice — all core features (transcription, AI reasoning, speaker diarization, semantic search) work with local models or cloud providers — including GPU-accelerated local Whisper on Metal, CUDA, and Vulkan (AMD/Intel)
Enterprise controls — enforce organization policy, company SSO and SCIM, and centrally managed Amazon Bedrock or Azure OpenAI access without distributing cloud keys
Public API & MCP — manage notes and transcriptions programmatically or connect your AI assistant via the MCP server

Quick start

git clone https://github.com/OpenWhispr/openwhispr.git
cd openwhispr
npm install
npm run dev

Requires Node.js 24+. See the full documentation for setup guides, platform-specific instructions, and build details.

The commands above run the desktop application, which remains at the repository root. The Expo mobile application lives in openwhispr-mobile with its own dependencies, lockfile, build configuration, and release process. See the mobile README for its setup instructions.

Documentation

Visit docs.openwhispr.com for:

Repo examples:

Custom ASR shim for Self-Hosted transcription against non-OpenAI-compatible ASR APIs

Tech stack

React 19, TypeScript, Tailwind CSS v4, Electron 41, better-sqlite3, whisper.cpp, sherpa-onnx, shadcn/ui

Star History

Contributing

We welcome contributions. Fork the repo, create a feature branch, and open a pull request. See the contributing guide for development setup and guidelines.

License

MIT — free for personal and commercial use.

Acknowledgments

OpenAI Whisper — speech recognition model powering local and cloud transcription
whisper.cpp — high-performance C++ implementation for local processing
NVIDIA Parakeet — fast multilingual ASR model
sherpa-onnx — cross-platform ONNX runtime for Parakeet inference
Hugging Face — model hub hosting Whisper, Parakeet, and embedding model weights
llama.cpp — local LLM inference for AI text processing
Electron — cross-platform desktop framework
React — UI component library
shadcn/ui — accessible components built on Radix primitives
Neon — serverless Postgres powering OpenWhispr Cloud

9.5K ·GitHub

Openwhispr

What is this?

OpenWhispr is an open-source, privacy-first voice-to-text dictation app for desktop. Press a hotkey, speak, and the text appears at your cursor, with extra features like an AI voice assistant, meeting transcription, and notes.

How do I install and run it?

Download a prebuilt build for your OS — macOS .dmg, Windows .exe, or Linux .AppImage/.deb/.rpm/.tar.gz — or run it from source, which requires Node.js 24+; full setup guides live at docs.openwhispr.com.

Do I need an API key for the AI features?

No API key is needed for core offline dictation since it can run fully on local models like Whisper or NVIDIA Parakeet. For cloud-based AI agent features (GPT-5, Claude, Gemini, Groq, OpenRouter) or faster cloud transcription, you bring your own key (BYOK).

Does it work the same on Intel Macs?

Not fully — on Intel Macs, live speaker identification and voice fingerprinting don't work because they depend on ONNX Runtime, which dropped macOS x86_64 binaries. Meetings still record and transcribe normally, but notes search falls back to keyword matching instead of semantic search.

Does my audio ever leave my device?

Not if you choose local models — fully offline transcription keeps audio on-device, and the app has no data collection or telemetry.

What happens during meeting transcription?

OpenWhispr auto-detects Zoom, Teams, and FaceTime calls and provides live speaker diarization with voice fingerprinting across meetings, plus calendar integration with Google, Microsoft, or Apple Calendar.

Can I connect my own AI assistant via MCP?

Yes — OpenWhispr ships an MCP server so you can manage notes and transcriptions programmatically or hook up any assistant that speaks the Model Context Protocol.

Can I transcribe existing audio or video files?

Yes, you can drag in files, batch-upload, or paste a YouTube/audio URL for transcription, with optional speaker detection.

Is there a mobile version?

Yes — a separate Expo-based mobile app lives in the openwhispr-mobile folder with its own dependencies, lockfile, and release process, distinct from the desktop app.

What are similar projects?

SCM, meetily, call.md, screenpipe, lipflow, get-it, holaOS, laya

Which topics is it in?

meeting-notes, groq, llamacpp, voice-assistant, byok, whisper, sso, onnx, speech-to-text, speech-recognition, note-taking, privacy-first

Creator: OpenWhispr
Size: 161.4 MB
Stars: 9.5K
Updated: CommitOct 16 Releasev1.10.3Oct 12
Age: 1y
Commits · 90 Days